CAFA Publications

Author(s): Gilligan‐Lunda, Erin K., Daniel S. Stich, Katherine E. Mills, Michael M. Bailey, and Joseph D. Zydlewski

Project PI: Stich
DOI: https://doi.org/10.1002/tafs.10299

American Shad Alosa sapidissima is an anadromous species with populations ranging along the U.S. Atlantic coast. Past American Shad stock assessments have been data limited and estimating system-specific growth parameters or instantaneous natural mortality (M) was not possible. This precluded system-specific stock assessment and management due to reliance on these parameters for estimating other population dynamics (such as yield per recruit). Furthermore, climate-informed biological reference points remain a largely unaddressed need in American Shad stock assessment. Population abundance estimates of American Shad and other species often rely heavily on M derived from von Bertalanffy growth function (VBGF) parameters. Therefore, we developed Bayesian hierarchical models to estimate coastwide, regional, and system-specific VBGF parameters and M using data collected from 1982 to 2017. We tested predictive performance of models that included effects of various climate variables on VBGF parameters within these models. System-specific models were better supported than regional or coast-wide models. Mean asymptotic length (L∞) decreased with increasing mean annual sea surface temperature (SST) and degree days (DD) experienced by fish during their lifetime. Although uncertain, K (Brody growth coefficient) decreased over the same range of lifetime SST and DD. Assuming no adaptation, we projected changes in VBGF parameters and M through 2099 using modeled SST from two climate projection scenarios (Representative Concentration Pathways 4.5 and 8.5). We predicted reduced growth under both scenarios, and M was projected to increase by about 0.10. It is unclear how reduced growth and increased mortality may influence population productivity or life history adaptation in the future, but our results may inform stock assessment models to assess those trade-offs.

Author(s): Cheng, Wei, A. Hermann, A. Hollowed, K. Holsman, K. Kearney, D. Pilcher, C. Stock, K. Aydin

Project PI: Hollowed
DOI: http://doi.org/10.1016/j.dsr2.2021.104975

In this study we present projected changes in the Eastern Bering Sea shelf (EBS) biophysical processes in response to climate forcing scenarios from the Coupled Model Intercomparison Phase 6 (CMIP6). These changes are obtained by dynamical downscaling using a Bering Sea regional model. Surface atmospheric and ocean boundary forcing from three Earth System Models (ESMs) in CMIP6, and a low and a high emission scenario of Shared Socioeconomic Pathway (SSP126 and SSP585) of each of the ESMs are considered. Ensemble mean results suggest that, contrary to an anticipated increase in ocean stratification under warming, diminishing ice cover in response to climate forcing and resultant reduced surface freshening weakens EBS stratification in the melt season. Modeled ensemble mean phytoplankton and zooplankton biomass on the EBS exhibits subsurface maxima during the growing season; the amplitude of these maxima decreases with warming, along with a reduction in primary productivity and oxygen concentration over much of the EBS water column. Phenology of both phytoplankton and zooplankton biomass on the EBS shifts earlier, leading to an increase (decrease) in biomass averaged between April–July (August–November), while annually averaged biomass decreases under warming. Projected changes of primary and secondary plankton biomass at the end of the 21st century are not well separated between the SSP126 and SSP585 scenario in light of the large across model spread under each scenario. The projected ensemble mean warming amplitude of the EBS summer bottom temperature is largely unchanged between results forced by the Coupled Model Intercomparison Phase 5 Representative Concentration Pathway 8.5 (CMIP5 RCP8.5) and CMIP6 SSP585 scenarios. Likewise, the reduction rate of annual mean phytoplankton and large zooplankton biomass are comparable between RCP8.5 and SSP585 projections, even though the absolute amplitudes of biomass are sensitive to modeling parameters such as the solar irradiance attenuation curve. Hence, within the Bering Sea dynamical downscaling framework, projected long-term warming trends in EBS bottom temperature and plankton biomass reduction rates are robust responses to climate forcing.

Author(s): Drenkard, E., C. Stock, A. Adcroft, M. Alexander, V. Balaji, S. J. Bograd, M. Butenschön, W. Cheng, E. Curchitser, E. Di Lorenzo, K. W. Dixon, R. Dussin, A. Haynie, M. Harrison, A. Hermann, A. Hollowed, K. Holsman, J. Holt, M. G. Jacox, C. Joo Jang, K. A. Kearney, B. A. Muhling, M. Pozo Buil, A. C. Ross, V. Saba, A. Britt Sandø, D. Tommasi, M. Wang.

Project PI: Hollowed
DOI: http://doi.org/10.1093/icesjms/fsab100

Efforts to manage living marine resources (LMRs) under climate change need projections of future ocean conditions, yet most global climate models (GCMs) poorly represent critical coastal habitats. GCM utility for LMR applications will increase with higher spatial resolution but obstacles including computational and data storage costs, obstinate regional biases, and formulations prioritizing global robustness over regional skill will persist. Downscaling can help address GCM limitations, but significant improvements are needed to robustly support LMR science and management. We synthesize past ocean downscaling efforts to suggest a protocol to achieve this goal. The protocol emphasizes LMR-driven design to ensure delivery of decision-relevant information. It prioritizes ensembles of downscaled projections spanning the range of ocean futures with durations long enough to capture climate change signals. This demands judicious resolution refinement, with pragmatic consideration for LMR-essential ocean features superseding theoretical investigation. Statistical downscaling can complement dynamical approaches in building these ensembles. Inconsistent use of bias correction indicates a need for objective best practices. Application of the suggested protocol should yield regional ocean projections that, with effective dissemination and translation to decision-relevant analytics, can robustly support LMR science and management under climate change.

Author(s): Essington, T. E., M. E. Matta, B. A. Black, T. E. Helser, P. D. Spencer.

Project PI: Hollowed
DOI: http://doi.org/10.1139/cjfas-2021-0046

Identifying changes in fish growth is important for accurate scientific advice used for fisheries management, because environmental change is affecting fish growth and size-at-age is a critical component of contemporary stock assessment methods. Growth-increment biochronologies are time series of growth-increments derived from hard parts of marine organisms that may reveal dynamics of somatic fish growth. Here we use time series of otolith increments of two fish stocks to fit and compare a biologically derived growth model and a generalized statistical model. Both models produced similar trajectories of annual growth trends, but the biologically based one was more precise and predicted smaller interannual fluctuations than the statistical model. The biologically based model strongly indicated covariance between anabolic and catabolic rates among individuals. Otolith size-at-age did not closely match fish length-at-age, and consequently the growth model could not accurately hindcast observed fish length-at-age. For these reasons, fitted growth dynamics from otolith biochronologies may best suited to identify growth rate fluctuations, understand past drivers of growth dynamics, and improve ecological forecast in the face of rapid environmental change.

Author(s): Hermann, A. J., K. Kearney, W. Cheng, D. Pilcher, K. Aydin, K. K. Holsman, A. B. Hollowed.

Project PI: Hollowed
DOI: http://doi.org/10.1016/j.dsr2.2021.104974

Three different global earth system models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) were used to explore anticipated changes in the Bering Sea under high (SSP126) and low (SSP585) carbon mitigation scenarios (i.e. low and high emission scenarios), via dynamical downscaling. A multivariate pattern analysis, based on Empirical Orthogonal Functions applied to monthly time series, reveals strong coupling of changes across several biophysical variables and the global forcing itself, on both yearly and multidecadal time scales. Rising air and ocean temperatures from the global models are strongly coupled with rising regional temperatures and reduced ice cover/thickness, as well as strong changes to the phenology of the plankton food chain, including reduced biomass of large zooplankton in the fall. This method ultimately provides a compact way to estimate the changes to many regional attributes under a variety of global change scenarios. Application of this method to a broad ensemble of the CMIP6 global model air temperatures suggests that compared to present conditions, the Bering Sea shelf bottom temperatures in July will warm by an average of ∼4 degrees C by the end of the 21st century under SSP585, as compared with ∼1 degrees C under SSP126, with greatest warming focused on the outer northern shelf.

Author(s): Kaplan, I. C., S. K. Gaichas, C. C. Stawitz, P. D. Lynch, K. N. Marshall, J. J. Deroba, M. Masi, J. K. T. Brodziak, K. Y. Aydin, K. Holsman, H. Townsend, D. Tommasi, J. A. Smith, S. Koenigstein, M. Weijerman, J. Link.

Project PI: Hollowed
DOI: http://doi.org/10.3389/fmars.2021.624355

Management strategy evaluation (MSE) is a simulation approach that serves as a “light on the hill” (Smith, 1994) to test options for marine management, monitoring, and assessment against simulated ecosystem and fishery dynamics, including uncertainty in ecological and fishery processes and observations. MSE has become a key method to evaluate trade-offs between management objectives and to communicate with decision makers. Here we describe how and why MSE is continuing to grow from a single species approach to one relevant to multi-species and ecosystem-based management. In particular, different ecosystem modeling approaches can fit within the MSE process to meet particular natural resource management needs. We present four case studies that illustrate how MSE is expanding to include ecosystem considerations and ecosystem models as ‘operating models’ (i.e., virtual test worlds), to simulate monitoring, assessment, and harvest control rules, and to evaluate tradeoffs via performance metrics. We highlight United States case studies related to fisheries regulations and climate, which support NOAA’s policy goals related to the Ecosystem Based Fishery Roadmap and Climate Science Strategy but vary in the complexity of population, ecosystem, and assessment representation. We emphasize methods, tool development, and lessons learned that are relevant beyond the United States, and the additional benefits relative to single-species MSE approaches.

Author(s): Punt, André E., M. G. Dalton, W. Cheng, A. J.Hermann, K. K.Holsman, T. P. Hurst, J. N.Ianelli, K. A. Kearney, C. R.McGilliard, D. J.Pilcher, M. Véron.

Project PI: Hollowed
DOI: http://doi.org/10.1016/j.dsr2.2021.104951

Climate-enhanced stock assessment models represent potentially vital tools for managing living marine resources under climate change. We present a climate-enhanced stock assessment where environmental variables are integrated within a population dynamics model assessment of biomass, fishing mortality and recruitment that also accounts for process error in demographic parameters. Probability distributions for the impact of the associated environmental factors on recruitment and growth can either be obtained from Bayesian analyses that involve fitting the population dynamics model to the available data or from auxiliary analyses. The results of the assessment form the basis for the calculation of biological and economic target and limit reference points, and projections under alternative harvest strategies. The approach is applied to northern rock sole (Lepidopsetta polyxystra), an important component of the flatfish fisheries in the Eastern Bering Sea. The assessment involves fitting to data on catches, a survey index of abundance, fishery and survey age-compositions and survey weight-at-age, with the relationship between recruitment and cold pool extent and that between growth increment in weight and temperature integrated into the assessment. The projections also allow for an impact of ocean pH on expected recruitment based on auxiliary analyses. Several alternative models are explored to assess the consequences of different ways to model environmental impacts on population demography. The estimates of historical biomass, recruitment and fishing mortality for northern rock sole are not markedly impacted by including climate and environmental factors, but estimates of target and limit reference points are sensitive to whether and how environmental variables are included in stock assessments and projections.

Author(s): Szuwalski, C.S., W. Cheng, R. Foy, A. Hermann, A. Hollowed, K. Holsman, J. Lee, W. Stockhausen, J. Zheng.

Project PI: Hollowed
DOI: http://doi.org/10.1016/j.dsr2.2021.104951

Crab populations in the eastern Bering Sea support some of the most valuable fisheries in the United States, but their future productivity and distribution are uncertain. We explore observed changes in the productivity and distribution for snow crab, Tanner crab, and Bristol Bay red king crab. We link historical indices of environmental variation and predator biomass with observed time series of centroids of abundance and extent of crab stock distribution; we also fit stock–recruit curves including environmental indices for each stock. We then project these relationships under forcing from global climate models to forecast potential productivity and distribution scenarios. Our results suggest that the productivity of snow crab is negatively related to the Arctic Oscillation (AO) and positively related to ice cover; Tanner crab’s productivity and distribution are negatively associated with cod biomass and sea surface temperature. Aspects of red king crab distribution and productivity appear to be related to bottom temperature, ice cover, the AO, and/or cod biomass. Projecting these relationships forward with available forecasts suggests that Tanner crab may become more productive and shift further offshore, red king crab distribution may contract and move north, and productivity may decrease for snow crab as the population contracts northward.

Author(s): Thorson, J. T., M. L. Arimitsu, L. A. K. Barnett, W. Cheng, L. B. Eisner, A.C. Haynie, A. J. Hermann, K. Holsman, D. G. Kimmel, M. W. Lomas, J. Richar. E. C. Siddon.

Project PI: Hollowed
DOI: http://doi.org/10.1111/ecog.05471

Ecosystems are increasingly impacted by human activities, altering linkages among physical and biological components. Spatial community reassembly occurs when these human impacts modify the spatial overlap between system components, and there is need for practical tools to forecast spatial community reassembly at landscape scales using monitoring data. To illustrate a new approach, we extend a generalization of empirical orthogonal function (EOF) analysis, which involves a spatio-temporal ecosystem model that approximates coupled physical, biological and human dynamics. We then demonstrate its application to five trophic levels for the eastern Bering Sea by fitting to multiple, spatially unbalanced datasets measuring physical characteristics (temperature measurements and climate-linked forecasts), primary producers (spring and fall size-fractionated chlorophyll-a), secondary producers (copepods), juveniles (age-0 walleye pollock), adult consumers (five commercially important fishes), human activities (seasonal fishing effort) and mobile predators (seabirds). We identify the spatial niche for each ecosystem component, as well as dominant modes of variability that are highly correlated with a known bottom–up driver of dynamics. We then measure spatial overlap between interacting variables (using Schoener's-D) and identify that age-0 pollock have decreased spatial overlap with copepods and increased overlap with adult pollock during warm years, and also that adult pollock have increased overlap with arrowtooth flounder and decreased overlap with catcher–processor fishing effort during these warm years. Given the warming conditions that are projected for the coming decade, the model forecasts increased prey and competitor overlap involving adult pollock (between age-0 pollock, adult pollock and arrowtooth flounder) and decreased overlap with the copepod forage base and with the catcher–processor fishery during future warming. We recommend that joint species distribution models be extended to incorporate ‘ecological teleconnections' (correlations between distant locations arising from known mechanisms) arising from behavioral adaptation by mobile animals as well as passive advection of nutrients and planktonic juvenile stages.

Author(s): Thorson, J. T., A. J. Hermann, K. Siwicke, M. Zimmermann.

Project PI: Hollowed
DOI: http://doi.org/10.1093/icesjms/fsaa236

Spatial management has been adopted worldwide to mitigate habitat impacts while achieving fisheries management objectives. However, there is little theory or practice for predicting the impact of spatial regulations on future fishery production; this would provide scientific basis for greater flexibility in fisheries management when balancing fishery and conservation goals. We propose that predicting changes in fishery production resulting from human activities within specific habitats is a “Grand Challenge” for habitat science in the coming decade(s). We then outline three difficulties in resolving this Grand Habitat Challenge, including: (i) stage-structured responses to habitat impacts, (ii) nonlocal responses, and (iii) mechanistic associations among habitat variables. We next discuss analytical approaches to address each difficulty, respectively: (i) ongoing developments for spatial demographic models; (ii) individual movement models and rank-reduction approaches to identify regional variability; (iii) causal analysis involving structural equation models. We demonstrate nonlocal effects in detail using a diffusion-taxis movement model applied to sablefish (Anoplopoma fimbria) in the Gulf of Alaska and discuss all three approaches for deep-sea corals. Despite isolated progress to resolve individual difficulties, we argue that resolving this Grand Habitat Challenge will require a coordinated commitment from science agencies worldwide.